---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Zidan_model_output_v12
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Zidan_model_output_v12

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co./indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8981
- Accuracy: 0.5818

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 220  | 1.0490          | 0.5091   |
| No log        | 2.0   | 440  | 0.9815          | 0.5182   |
| 1.0255        | 3.0   | 660  | 0.9462          | 0.5455   |
| 1.0255        | 4.0   | 880  | 0.9429          | 0.5545   |
| 0.862         | 5.0   | 1100 | 0.9189          | 0.5636   |
| 0.862         | 6.0   | 1320 | 0.9143          | 0.5727   |
| 0.7694        | 7.0   | 1540 | 0.9051          | 0.5545   |
| 0.7694        | 8.0   | 1760 | 0.9033          | 0.5545   |
| 0.7694        | 9.0   | 1980 | 0.9024          | 0.5636   |
| 0.7092        | 10.0  | 2200 | 0.9031          | 0.5636   |
| 0.7092        | 11.0  | 2420 | 0.9067          | 0.5909   |
| 0.65          | 12.0  | 2640 | 0.8994          | 0.5636   |
| 0.65          | 13.0  | 2860 | 0.8963          | 0.5727   |
| 0.63          | 14.0  | 3080 | 0.8971          | 0.5727   |
| 0.63          | 15.0  | 3300 | 0.8981          | 0.5818   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1